Set `--action_env=CLANG_CUDA_COMPILER_PATH` after cuda_nvcc configuration
Add `--config=cuda_clang` when `--nouse_cuda_nvcc` flag set
PiperOrigin-RevId: 678873849
If `--use_cuda_nvcc` flag is set the NVCC compiler driver will be used to build the CUDA code (default behavior). Otherwise, if the flag `--nouse_cuda_nvcc` is set, only the clang compiler will be used to build the CUDA code (effectively disabling NVCC).
Mark `--use_clang` flag as deprecated.
Refactor `.bazelrc` configs to match the new flag and to cleanup all previous confusing names.
PiperOrigin-RevId: 678332548
1) Hermetic CUDA rules allow building wheels with GPU support on a machine without GPUs, as well as running Bazel GPU tests on a machine with only GPUs and NVIDIA driver installed. When `--config=cuda` is provided in Bazel options, Bazel will download CUDA, CUDNN and NCCL redistributions in the cache, and use them during build and test phases.
[Default location of CUNN redistributions](https://developer.download.nvidia.com/compute/cudnn/redist/)
[Default location of CUDA redistributions](https://developer.download.nvidia.com/compute/cuda/redist/)
[Default location of NCCL redistributions](https://pypi.org/project/nvidia-nccl-cu12/#history)
2) To include hermetic CUDA rules in your project, add the following in the WORKSPACE of the downstream project dependent on XLA.
Note: use `@local_tsl` instead of `@tsl` in Tensorflow project.
```
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_json_init_repository.bzl",
"cuda_json_init_repository",
)
cuda_json_init_repository()
load(
"@cuda_redist_json//:distributions.bzl",
"CUDA_REDISTRIBUTIONS",
"CUDNN_REDISTRIBUTIONS",
)
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_redist_init_repositories.bzl",
"cuda_redist_init_repositories",
"cudnn_redist_init_repository",
)
cuda_redist_init_repositories(
cuda_redistributions = CUDA_REDISTRIBUTIONS,
)
cudnn_redist_init_repository(
cudnn_redistributions = CUDNN_REDISTRIBUTIONS,
)
load(
"@tsl//third_party/gpus/cuda/hermetic:cuda_configure.bzl",
"cuda_configure",
)
cuda_configure(name = "local_config_cuda")
load(
"@tsl//third_party/nccl/hermetic:nccl_redist_init_repository.bzl",
"nccl_redist_init_repository",
)
nccl_redist_init_repository()
load(
"@tsl//third_party/nccl/hermetic:nccl_configure.bzl",
"nccl_configure",
)
nccl_configure(name = "local_config_nccl")
```
PiperOrigin-RevId: 662981325
When `build_gpu_plugin` is true, three wheels will be produced (jaxlib, jax-cuda-pjrt and jax-cuda-plugin). If they are editable, they need to be placed in subdirectories to avoid overwrite.
Tested on GPU. After the editable wheels are built, they can be installed with `pip install -e /jax/dist/jax_gpu_pjrt /jax/dist/jaxlib /jax/dist/jax_gpu_plugin`.
PiperOrigin-RevId: 660984311
The plugin is released and the flag is no longer needed.
Also set default value of enable_gpu to False. enable_gpu will be removed in the next change.
PiperOrigin-RevId: 660059432
This lets us avoid bundling a whole another copy of LLVM with JAX packages
and so we can finally start building Mosaic GPU by default.
PiperOrigin-RevId: 638569750
With this change, `python3 build/build.py --enable_cuda --build_gpu_plugin --gpu_plugin_cuda_version=12` will generate three wheels:
| |size|wheel name |
|----------------------|----|-------------------------------------------------------------------------|
|jaxlib w/o cuda kernels|76M |jaxlib-0.4.20.dev20231101-cp310-cp310-manylinux2014_x86_64.whl |
|cuda pjrt |73M|jax_cuda12_pjrt-0.4.20.dev20231101-py3-none-manylinux2014_x86_64.whl |
|cuda kernels |6.6M|jax_cuda12_plugin-0.4.20.dev20231101-cp310-cp310-manylinux2014_x86_64.whl|
The size of jaxlib with cuda kernels and pjrt is 119M.
The cuda kernel wheel contains all the cuda kernels. A plugin_setup.py and plugin_pyproject.toml are added for this new pacakge.
PiperOrigin-RevId: 579861480
Add a --verbose option that logs all shell() commands run by the script.
Remove some Python 2 backward compatibility logic related to urllib and shutil.
Enable debug logging on Windows wheel builds.
Also include setuptools in the build requirements and test for its presence in build.py.
- Add a py extension to call the custom call C API.
- Change the implementation of register_custom_call_target to store handlers for the custom call targets and delays the registration until the handler for a xla platform is registered.
- Change register_plugin to load PJRT plugin when register_pluin is called (instead of when a client is created), and let it return the PJRT_Api* loaded.
- Delay calling discover_pjrt_plugins() and register_pjrt_plugin_factories_from_env() until the first time backends() is called.
PiperOrigin-RevId: 568265745
Add a build wheel, pyproject.toml and setup.py.
The directory structure in jax repo is:
jax/
└── plugins/
└── cuda/
├── __init__.py
├── pyproject.toml
└── setup.py
Installed package structure is:
jax_plugins/
└── xla_cuda_cu12/
├── __init__.py
└── xla_cuda_plugin.so
The major cuda version will be part of the package name.
The plugin wheel can be built with command:
python3 build/build.py --enable_cuda --build_gpu_plugin --gpu_plugin_cuda_version=12 --bazel_options="--override_repository=xla=$HOME/xla"
PiperOrigin-RevId: 565187954
The jaxlib wheel build currently uses `python setup.py bdist_wheel` to construct the wheel. Change it to use `python -m build -w` instead.
To avoid Python getting confused between the directory named `build` in the bazel tree and the Python `build` module, move `build_wheel.py` into `jaxlib/tools`.
PiperOrigin-RevId: 548133811
--
57af5360a1ca1356dbf7760c76e241f7134ef6dd by Jake VanderPlas <jakevdp@google.com>:
[Rollback] Update required Python version to 3.9
PiperOrigin-RevId: 528905991
